Japanese journal of radiology
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The applications of artificial intelligence (AI), including machine learning and deep learning, in the field of pancreatic disease imaging are rapidly expanding. AI can be used for the detection of pancreatic ductal adenocarcinoma and other pancreatic tumors but also for pancreatic lesion characterization. In this review, the basic of radiomics, recent developments and current results of AI in the field of pancreatic tumors are presented. Limitations and future perspectives of AI are discussed.
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We aimed to evaluate the feasibility of 3D broadband inversion-recovery-prepared ultrashort echo-time (3D IRP UTE) imaging for assessing ossification of the posterior longitudinal ligament (OPLL). ⋯ 3D IRP UTE imaging may be useful for assessing OPLL.
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Improvements in positron emission tomography (PET) technology have contributed to increased diagnostic accuracy in patients with large-vessel vasculitis (LVV) over the last decades. Many systematic reviews and meta-analyses were conducted, and earlier diagnosis by 18F-FDG PET can be made in patients suspected of having LVV. ⋯ In most patients, disease activity cannot be monitored by laboratory tests alone; therefore, glucose metabolism may be a source for possible biomarkers. In this review, we present current concepts regarding 18F-FDG PET/CT imaging standards.
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Bibliometric analysis is a quantitative assessment of the academic literature in a particular field. The aim of our study was to characterize the 100 top-cited articles regarding transarterial chemoembolization (TACE) for the treatment of hepatocellular carcinoma (HCC). ⋯ We performed an analysis of the 100 top-cited articles dealing with TACE for HCC, presenting a detailed list of the most influential and historically significant papers. Japan was the country that produced the most top-cited articles, highlighting its key contribution to this field of the literature.
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Review
Chest computed tomography findings of COVID-19 pneumonia: pictorial essay with literature review.
Available information on chest Computed Tomography (CT) findings of the 2019 novel coronavirus disease (COVID-19) is constantly evolving. Ground glass opacities and consolidation with bilateral and peripheral distribution were reported as the most common CT findings, but also less typical features could be identified. All radiologists should be aware of the imaging spectrum of the COVID-19 pneumonia and imaging changes in the course of the disease. Our aim is to display the chest CT findings at first assessment and follow-up through a pictorial essay, to help in the recognition of these features for an accurate diagnosis.